labparse

One parser for lab instrument exports. Point it at the file your plate reader, spectrometer, or other bench instrument spat out, and get back a tidy table: one row per reading, with well, row, column, cycle, time in seconds, and value.

import labparse

result = labparse.parse("growth.asc")
result.data            # tidy pandas DataFrame
result.wide()          # one column per well
result.save_csv("tidy.csv")

labparse growth.asc --out tidy.csv
labparse kinetic.txt --wide

The trick: formats are learned once, then free forever

Every instrument exports its own hostile format, and most labs end up writing throwaway parsing scripts for each one. labparse works differently:

1. Known formats parse instantly using bundled recipes, small JSON descriptions of a format that a deterministic engine executes.
2. When labparse meets a format it does not know, it shows the raw file to your own LLM once, and the LLM writes a new recipe.
3. The recipe is only accepted if it actually parses your file. A wrong recipe is rejected and retried, it can never silently produce bad data.
4. Accepted recipes are cached in ~/.labparse/recipes, so each format costs at most one LLM call ever, and cached formats parse offline.

No LLM configured? Everything with a bundled or cached recipe still works, unknown formats give a clear message instead.

Bundled formats

• Tecan plate reader ASCII exports (.asc, repeated well grids)
• Molecular Devices SoftMax Pro / SpectraMax kinetic exports (.txt)
• Generic wide tables, CSV or TSV, with one column per well
• Generic long tables, CSV, with a well column and a value column
• Excel workbooks containing a well header row or a plate grid (pip install labparse[excel])

Recipes are plain JSON. You can read them, edit them, share them with your lab, and drop new ones into the recipe folder. labparse --list-recipes shows everything installed.

Bring your own model (for learning new formats)

labparse looks for a language model in this order and uses the first one it finds:

1. claude CLI (an active Claude Code login)
2. codex CLI
3. ANTHROPIC_API_KEY
4. OPENAI_API_KEY (set OPENAI_BASE_URL for any OpenAI compatible server)

Control it with --llm off, --llm claude, or the LABPARSE_LLM environment variable.

Install

pip install labparse

Excel support: pip install labparse[excel]

Output columns

column	meaning
well	normalized well id, A1 to P24
row	plate row letter
col	plate column number
cycle	reading number in file order, starts at 1
time_s	seconds, parsed from h:mm:ss or numeric time fields, NaN when the format has no time
value	the measurement

Extra columns from the instrument, like temperature, are kept.

Author

Built by Paul Crinigan, AI Apps API. Full documentation lives on the labparse page, part of the free AI science tools collection at learnhowtoscience.com.

MIT licensed.